
from config.model_config import get_base_open_ai
from config.embedding_config import bge_model_name

client = get_base_open_ai()
response = client.embeddings.create(
    model=bge_model_name, #填写需要调用的模型编码
    input=[
        "美食非常美味，服务员也很友好。",
        "这部电影既刺激又令人兴奋。",
        "阅读书籍是扩展知识的好方法。"
    ],
)
#CreateEmbeddingResponse(data=[Embedding(embedding=[0.07266125082969666, -0.002732323482632637, -0.042284294962882996, 0.014299466274678707, 0.004032339435070753, 0.020839659497141838, -0.023128438740968704, -0.05462848022580147, -0.032094795256853104, -0.014248715713620186, 0.011053544469177723, -0.008885017596185207, 0.03700392693281174, 0.024290988221764565, 0.009557041339576244, 0.037919290363788605, 0.01683812215924263, -0.011593650095164776, -0.008782942779362202, -0.023458708077669144, 0.06256663054227829, -0.025434205308556557, -0.0498521663248539, -0.048554643988609314, -0.05943477526307106, -0.012803941033780575, 0.04553152993321419, -0.008428136818110943, -0.019338922575116158, 0.00040007461211644113, -0.008105030283331871, -0.023496706038713455, 0.004031064920127392, -0.05077772215008736, -0.015478121116757393, 0.02251538075506687, -0.0028896310832351446, -0.003510629292577505, 0.030532890930771828, -0.0296147670596838, 0.005370269063860178, -0.004128909204155207, 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object='embedding')],
# model='bge-large-zh-v1.5', object='list', usage=Usage(prompt_tokens=48, total_tokens=48), model_replica='bge-large-zh-v1.5-0')
# print(response)
# print(response.data)

# 3 ge
print(len(response.data))

print(response.data[0])


